With the entire human genome now almost completely decoded, attention is shifting towards individual genetic variation. Most of this variation consists of single nucleotide polymorphisms (SNPs), which can account for heritable inter-individual differences in, for example, disease susceptibility and response to medication. Aging is a major risk factor for most common human diseases. The identification of SNPs in candidate genes and the assessment of their potential functional impact on aging-related phenotypes will be important in assessing genetic components of aging, including exceptionally healthy aging. Optimal study populations in this respect are those in which aging-related phenotypes can be defined in terms of their progression from middle age onwards, rather than as snapshots in time. The objective of this proposal is to further optimize a previously developed SNP discovery method, Two-Dimensional Gene Scanning (TDGS), to comprehensively analyze SNPs in multiple candidate genes in large, aging populations. The validity of this approach will be assessed through association analysis, in a case control manner, of all possible SNPhaplotypes of a selection of nuclear and mitochondrial genes involved in musculoskeletal function in a population of 226 Mexican American individuals of an ongoing longitudinal study of aging (San Antonio Longitudinal Study of Aging; SALSA). The results are expected to enrich the ongoing study with a genetic component for this particular phenotype and to demonstrate the validity of TDGS as a high-throughput platform to screen aging populations for all possible SNPs in hundreds and ultimately thousands of candidate genes (comprehensive candidate approach).